Personalizing Care Through Robotic Assistance and Clinical Supervision

Area of Science:

• Robotics and Artificial Intelligence in Healthcare
• Human-Robot Interaction
• Cognitive Systems for Assistive Technologies

Background:

• The World Health Organization (WHO) predicts a global healthcare professional shortage by 2030, impacting patient care and economies.
• Assistive robotics research is growing, offering intelligent solutions for healthcare and social assistance to mitigate workforce deficits.
• A key challenge for assistive robots is adapting to diverse situations and personalizing interactions based on user contexts and preferences.

Purpose of the Study:

• To present a novel cognitive system for assistive robots utilizing artificial intelligence (AI) for enhanced decision-making support for healthcare assistants.
• To integrate AI-based knowledge representation, reasoning, and automated planning to create adaptive robotic behaviors.
• To develop a human-in-the-loop continuous assistance procedure for patient evaluation and management, dynamically adjusting robot interactions.

Main Methods:

• Development of a cognitive system integrating AI features: knowledge representation and reasoning, and automated planning.
• Implementation of a human-in-the-loop procedure for continuous patient assistance and clinician support.
• Deployment in a realistic assistive scenario to evaluate the system's feasibility in supporting clinicians managing diverse patient needs.

Main Results:

• Demonstrated the feasibility of the cognitive system in a realistic assistive scenario.
• Showcased the system's ability to support clinicians in managing multiple patients with varying conditions.
• Validated the dynamic adaptation of robot behaviors to specific patient needs and interaction abilities.

Conclusions:

• The novel cognitive system effectively supports healthcare assistants by leveraging AI for decision-making.
• The integration of knowledge representation, reasoning, and automated planning enables adaptive robot behaviors tailored to individual patients.
• This approach offers a viable solution to enhance patient care and address healthcare workforce shortages through intelligent assistive robotics.